Abstract
We describe a speech enhancement algorithm which leads to significant quality and intelligibility improvements when used as a preprocessor to a low bit rate speech coder. This algorithm was developed in conjunction with the mixed excitation linear prediction (MELP) coder which, by itself, is highly susceptible to environmental noise. The paper presents novel as well as known speech and noise estimation techniques and combines them into a highly effective speech enhancement system. The algorithm is based on short-time spectral amplitude estimation, soft-decision gain modification, tracking of the a priori probability of speech absence, and minimum statistics noise power estimation. Special emphasis is placed on enhancing the performance of the preprocessor in nonstationary noise environments.
Highlights
A Noise Reduction Preprocessor for Mobile Voice CommunicationReceived 15 September 2003; Revised 20 November 2003; Recommended for Publication by Piet Sommen
With the advent and wide dissemination of mobile voice communication systems, telephone conversations are increasingly disturbed by environmental noise
In order to evaluate these gain functions, one must first estimate the noise power spectrum λd. This is often done during periods of speech absence as determined by a voice activity detector (VAD), or, as we will show below using the minimum statistics [11] approach
Summary
Received 15 September 2003; Revised 20 November 2003; Recommended for Publication by Piet Sommen. We describe a speech enhancement algorithm which leads to significant quality and intelligibility improvements when used as a preprocessor to a low bit rate speech coder. This algorithm was developed in conjunction with the mixed excitation linear prediction (MELP) coder which, by itself, is highly susceptible to environmental noise. The paper presents novel as well as known speech and noise estimation techniques and combines them into a highly effective speech enhancement system. The algorithm is based on short-time spectral amplitude estimation, soft-decision gain modification, tracking of the a priori probability of speech absence, and minimum statistics noise power estimation. Keywords and phrases: speech enhancement, noise reduction, speech coding, spectral analysis-synthesis, minimum statistics
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
